Digital ink-based search

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to the following copending U.S. patent applications, assigned to the assignee of the present application, filed concurrently herewith and hereby incorporated by reference: “Integrated Platform for User Input of Digital Ink,” U.S. patent application Ser. No. 11/821,870, and “Unified Digital Ink Recognition,” U.S. patent application Ser. No. 11/821,858.

BACKGROUND

Digital ink is becoming an important media for users to interact with computer applications. However, traditional search technologies are usually based on text, not on digital ink.

While text-based searching is often valuable, there are many kinds of data and information that cannot be described accurately and/or easily by text, such as shapes and sketches. For example, consider a user that wants to find a certain shape from a program's shape repository. The user may not know the program's text name for the shape, and thus may have trouble finding that shape, even though the user can easily sketch a similar shape easily with digital ink. Similarly, a sketch or other image/picture (e.g., a Word Art item) may be found via a text search with the appropriate text, but if the needed text is not known or intuitive to a user, a text search is not an effective way to find what the user wants.

SUMMARY

This Summary is provided to introduce a selection of representative concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used in any way that would limit the scope of the claimed subject matter.

Briefly, various aspects of the subject matter described herein are directed towards a technology by which digital ink received as input is used to search for non-character items (e.g., shapes) corresponding to the digital ink. Digital ink is sent to a unified digital ink recognizer that returns a recognition result as a character or another type of digital ink. When the recognition result is a character, the character is used in a keyword search to find one or more corresponding non-character items, e.g., from a data store. When the recognition result is a non-character item, the non-character item is provided as the search result, without keyword searching. In addition to shapes, other non-character items include handwritten gestures or drawn pictures.

For example, if the recognizer returns a character, the keyword search may return any item in which that character appears. Alternatively, the character can be used to build the keyword for a search. If instead the recognizer returns a non-character item such as a shape, the item may be used as the search result. The search result may appear as one or more visible representations of the corresponding item or items, such as in a result panel associated with a user interface into which the digital ink was input. Alternatively, the search result may be provided as corresponding information to a software program for which the item is being searched.

Other advantages may become apparent from the following detailed description when taken in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements and in which:

<figref idrefs="DRAWINGS">FIG. 1</figref> is a block diagram representative of example components used to build a unified digital ink recognizer.

<figref idrefs="DRAWINGS">FIG. 2</figref> is a block diagram representative of example components within a set of one or more core algorithms that may be used in building a unified digital ink recognizer.

<figref idrefs="DRAWINGS">FIG. 3A</figref> is a visual representation of a core algorithm that recognizes a new item via nearness to a class within a recognition model built during training.

<figref idrefs="DRAWINGS">FIG. 3B</figref> is a block diagram representing recognition of a new item.

<figref idrefs="DRAWINGS">FIG. 4</figref> is a flow diagram representing example steps that may be taken when building a unified digital ink recognizer.

<figref idrefs="DRAWINGS">FIGS. 5-14</figref> are representations of some example items that may be recognized from a sketch via a unified digital ink recognizer.

<figref idrefs="DRAWINGS">FIGS. 15-18</figref> are representations of some example user input may be recognized and searched.

<figref idrefs="DRAWINGS">FIG. 19</figref> is a block diagram representing example components for searching for custom items based on user input.

<figref idrefs="DRAWINGS">FIG. 20</figref> is a flow diagram representing example logic for searching for custom items based on user input and providing a search result.

<figref idrefs="DRAWINGS">FIG. 21</figref> shows an illustrative example of a general-purpose network computing environment into which various aspects of the present invention may be incorporated.

DETAILED DESCRIPTION

Various aspects of the technology described herein are generally directed towards digital ink based search technology that can be used to find items such as shapes, sketches and so forth efficiently and naturally. In one aspect, digital ink is used as input to search information directly. For example, as is known, digital ink is input naturally by user's handwriting, and can be used to represent different kinds of information intuitively and effectively. As will be understood, the advantages of digital ink input are leveraged herein to make digital ink-based searching more intuitive, natural, effective and efficient in certain areas relative to text based searching.

While various examples herein are primarily directed to differentiating between characters and shapes to search for shapes, such as with respect to a diagramming program such as Microsoft® Visio®, any handwritten input may be differentiated and/or benefit from the search technology described herein, including handwritten characters, sketched shapes, handwritten gestures and/or drawn pictures or the like. Further, while an example implementation of a unified digital ink recognizer is described herein that can among other aspects differentiate between characters and shapes, other implementations of a unified digital ink recognizer may be used.

As such, the present invention is not limited to any particular embodiments, aspects, concepts, structures, functionalities or examples described herein. Rather, any of the embodiments, aspects, concepts, structures, functionalities or examples described herein are non-limiting, and the present invention may be used various ways that provide benefits and advantages in computing, and digital ink in general.

Example Unified Digital Ink Recognizer

As described below with reference to <figref idrefs="DRAWINGS">FIGS. 1-4</figref>, a unified digital ink recognizer <b>102</b> is built. As part of the building process, a dataset of items that are to be recognized by the recognizer <b>102</b> is defined. For example, one such dataset comprises a set of Chinese characters and shapes, and contains 9,119 Chinese characters, corresponding to the Unicode range from 0x4e00 to 0x9FA5 (seldom used characters are removed), along with other custom shapes, corresponding to <figref idrefs="DRAWINGS">FIGS. 5-14</figref>, respectively. Further example shapes that may be recognized are represented in the aforementioned U.S. patent application entitled “Unified Digital Ink Recognition.”

For the shape set, the private use area of Unicode that can be customized, ranging from Unicode 0xF000 to 0xF0FF, is used. For building a unified digital ink recognizer, any item to be recognized can be assigned with a Unicode value from the private use area of Unicode, although an item with an already-assigned Unicode values (e.g., a character) can use that value.

To build the unified digital ink recognizer <b>102</b>, a learning based pattern recognition approach is used, as generally represented by the example components shown in <figref idrefs="DRAWINGS">FIG. 1</figref>. In general, this approach builds a classifier according to the features of different classes of items to be recognized. Via feature extraction, the features of each class of items are extracted from a collection of samples for that class.

With the classifier, given a new item to be recognized, the features of the item are matched with the feature of an existing class, which means the new item is recognized as belonging to that class.

One aspect of building a digital ink recognizer <b>102</b> with this approach is data collection of digital ink samples for each item in the defined dataset to be recognized by the digital ink recognizer <b>102</b>. In the implementation represented in <figref idrefs="DRAWINGS">FIG. 1</figref>, the digital ink samples <b>102</b> are divided into three different datasets, comprising a training set <b>106</b>, a testing set <b>110</b> and a tuning set <b>108</b>. The training set <b>106</b> is used for building a recognizer model <b>112</b>, the testing set <b>110</b> for evaluating the recognizer model <b>112</b>, and the tuning set <b>108</b> for tuning the recognizer model <b>112</b> to improve its accuracy. In one example implementation, for building the recognizer model <b>112</b>, five-hundred digital ink samples of handwriting were collected for each Chinese character in the training set, and one-hundred digital ink sketch samples were collected for each shape in the training set.

Based on the digital ink samples <b>104</b>, a first mechanism (process step) <b>114</b> develops and/or selects a set of one or more core algorithms <b>116</b> for use in extracting the features of the training set <b>106</b> to build the digital ink recognizer model <b>112</b> according to the extracted features. The developed core algorithms are performed on the training set <b>106</b> to build the digital ink recognizer model <b>112</b>.

More particularly, a recognition algorithm is used to build the recognizer model (classifier) <b>112</b> for the items to be recognized. As represented in <figref idrefs="DRAWINGS">FIG. 2</figref> via blocks <b>202</b> and <b>204</b>, for each selected training sample <b>206</b> of a set of training samples <b>106</b>, the core algorithm <b>116</b> includes a feature extraction mechanism <b>208</b> that extracts a set of features <b>210</b>. Further processing <b>212</b> may be performed on the feature set <b>210</b>, such as feature selection (e.g., for nearest neighbor recognition, described below with reference to <figref idrefs="DRAWINGS">FIG. 3</figref>) into selected feature set <b>214</b>. The feature set <b>214</b> is then combined with other such feature data for this sample's class to build (block <b>216</b>) the recognizer model <b>112</b>, by adjusting the combined feature data of the class to which this sample belongs based on the feature set <b>214</b>.

As is known, there are many existing and possible recognition algorithms which may be used to build a recognition system, including nearest neighbor classification (sometimes referred to as k-nearest neighbor, or KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM), and so forth. In one implementation of the unified digital ink recognition system, nearest neighbor classification is used to recognize digital ink.

A primary concept in nearest neighbor classification is to use one point in multi-dimensional space to represent each class of samples, such as classes A-C as generally represented in <figref idrefs="DRAWINGS">FIG. 3A</figref>. In such an example, the class data is thus a set of coordinates in multiple (two or more) dimensional space.

After the recognizer model <b>112</b> is built, when a new item “New Item” is to be recognized, that item is also represented by a point in this space. As represented in <figref idrefs="DRAWINGS">FIG. 3B</figref>, a search algorithm <b>330</b> performs computations (e.g., searches for a nearest neighbor) to find the nearest point relative to this new item's point, and recognizes this item as belonging to the class that is represented by the found search result, whereby the recognition result <b>332</b> (e.g., a Unicode value) is output. In the example of <figref idrefs="DRAWINGS">FIG. 3A</figref>, (in which only three classes are shown, and in only two dimensions for purposes of simplicity), it is readily apparent that the new item is nearest to the Class B, and thus would be recognized as whatever Unicode value corresponded to the Class B.

Returning to <figref idrefs="DRAWINGS">FIG. 1</figref>, the accuracy and efficiency of the unified digital ink recognizer model <b>112</b> may be evaluated via an evaluation mechanism <b>118</b> that operates using the testing set <b>116</b> of digital ink samples. Further, according to the evaluation results <b>119</b>, some error analysis may be performed (block <b>120</b>), by which the unified recognizer model <b>112</b> may be improved with the tuning set of digital ink samples <b>108</b>. As represented via decision diamond <b>122</b>, the process may be performed over and over to optimize the accuracy and efficiency of the unified recognizer model <b>112</b>, until, for example, the evaluation results indicate an acceptable recognizer.

When complete, a unified digital ink recognizer <b>102</b> is provided, comprising the core algorithm or algorithms and the recognizer model <b>112</b>. In one implementation, the unified digital ink recognizer can recognize digital ink of handwriting (e.g., Chinese characters) and sketching shapes (including sketched graphs). As a result, whether the user inputs a Chinese character by handwriting or inputs a shape by sketching, the unified digital ink recognizer correctly interprets the digital ink of the user's input as a character or as a shape.

<figref idrefs="DRAWINGS">FIG. 4</figref> summarizes how the unified digital ink recognition technology is built so as to uniformly recognize different kinds of information represented by digital ink, beginning at step <b>402</b> which represents defining the dataset of items to be recognized, and collecting the digital ink samples for those items. Step <b>404</b> represents dividing the digital ink samples into the training set, testing set and tuning set. Note that the samples may be divided randomly, or based on some other criteria, such as to put similar looking items in the tuning set. Step <b>406</b> represents selecting the core algorithms, e.g., determining which features to extract, and for nearest neighbor classification, which should be selected from those features, how much weight to give each feature, and so forth.

Step <b>408</b> represents using a feature extraction algorithm to extract the features from each selected item in the training set, with step <b>410</b> representing the feature selection algorithm, and step <b>412</b> representing the building of the recognizer model, e.g., processing the feature data of each selected item as needed to adjusting the feature data for the class [the class is identified by the Unicode value, the selected item is belonging to the class] in the recognizer model (such as representing multi-dimensional coordinates).

Step <b>414</b> represents the evaluation of the accuracy and/or efficiency using the testing set of digital ink samples. Based on an error analysis at step <b>416</b> as to how accurate and/or efficient the model is, samples from the tuning set may be applied at step <b>416</b> in an attempt to better optimize the recognizer. Step <b>418</b> represents repeating any or all of steps <b>406</b>, <b>408</b>,<b>410</b>, <b>412</b>, <b>414</b> and <b>416</b> for further optimization. Note that the evaluation at step <b>414</b> may be used to determine whether further optimization is necessary. Further, note that a model that is less accurate and/or efficient than another model may be discarded until the best model of those evaluated is determined.

Digital Ink-Based Search

Turning to <figref idrefs="DRAWINGS">FIGS. 15-20</figref>, there is exemplified therein a way to use digital ink to search information directly, referred to herein as digital ink based search. For example, as shown in <figref idrefs="DRAWINGS">FIGS. 15-18</figref>, Microsoft® Visio® shapes may be searched via digital ink input to a software program user interface panel <b>1502</b>.

As described above, the unified digital ink recognizer <b>102</b> is built to recognize a user's input as a character (e.g., a Chinese character) or a custom item, which in this example corresponds to a Visio® shape. If as in the representations <b>1500</b> and <b>1600</b> of <figref idrefs="DRAWINGS">FIGS. 15 and 16</figref>, respectively, the digital ink is input such that it is interpreted as a Chinese character, then the Chinese character is used as a keyword to search the related Visio shapes. As can be seen in these examples, when the user handwrites a Chinese character “<img id="CUSTOM-CHARACTER-00001" he="3.13mm" wi="3.89mm" file="US08094939-20120110-P00001.TIF" alt="custom character" img-content="character" img-format="tif" orientation="portrait" inline="no" />” or “<img id="CUSTOM-CHARACTER-00002" he="3.13mm" wi="2.46mm" file="US08094939-20120110-P00002.TIF" alt="custom character" img-content="character" img-format="tif" orientation="portrait" inline="no" />” for searching, then the related shapes whose keywords contain this Chinese character are returned as search result.

The search results are returned in the panel <b>1504</b> in <figref idrefs="DRAWINGS">FIGS. 15 and 16</figref>, respectively.

If instead as represented in the representations <b>1700</b> and <b>1800</b> of <figref idrefs="DRAWINGS">FIGS. 17 and 18</figref>, respectively, the input digital ink is interpreted as a shape, then the recognized shape may be used to provide the result directly. As can be seen in these examples, when the user sketches a triangle or polygon (e.g., pentagon) for searching, then the corresponding shape that the digital ink was recognized as is returned as a search result.

In general, the user may then drag a result from the results panel <b>1504</b> to the program into which the custom item (e.g., shape) is being input. However, other ways to handle the data are feasible. For example, note that in <figref idrefs="DRAWINGS">FIGS. 15</figref>, <b>17</b> and <b>18</b> only one recognition result is found for the user input; in such an event, rather than showing the single recognition result in a results panel <b>1504</b>, the shape can be made to directly appear in the program to which shapes are being used. For example, a user may receive a pop-up input search panel by right-clicking while in the diagramming program at the location an inserted shape is desired, and the user may automatically have the single shape inserted at that location, or if multiple shapes are returned (<figref idrefs="DRAWINGS">FIG. 16</figref>) may select from among those shapes for insertion at that location. Alternatively, recognized characters can provide one or more shapes in a result panel, while directly recognized shapes can be automatically inserted.

<figref idrefs="DRAWINGS">FIG. 19</figref> is a block diagram representation of the general operation of digital ink based search, in which a user inputs data (data block <b>1902</b>), such as into the input panel <b>1502</b>. When the input is complete, (e.g., by explicit user request or after a pen-up event that starts a timer reaches a timeout threshold), the digital ink is sent to the unified digital ink recognizer <b>102</b>, which produces a recognition result <b>1904</b>.

Search logic <b>1906</b> (such as the logic exemplified in <figref idrefs="DRAWINGS">FIG. 20</figref>) then determines based on the recognition result (character or custom item) whether to perform a keyword search to return a result <b>1910</b>, e.g., using an item (e.g., shape) data store <b>1908</b>, or whether to directly return the corresponding item as a result <b>1910</b>. Note that as used herein “directly” generally means without keyword searching, and does not necessarily mean that the Unicode value itself is returned to the panel and/or program into which the item is to be inserted, e.g., the Unicode value is typically first mapped to an image for outputting, and/or to a shape (object) identifier for the program in use. Mapping to an object identifier may occur with respect to a drag-and-drop operation or may be performed by the program itself.

<figref idrefs="DRAWINGS">FIG. 20</figref> provides example steps that may be taken by the search logic <b>1906</b> to produce an item (e.g., shape) result set based on a character or item recognition result. Step <b>2002</b> represents receiving the digital ink input to recognize, which may be a character or other (non-character) item.

If an item was recognized at step <b>2004</b>, step <b>2004</b> branches to step <b>2014</b> where the item (e.g., shape) is used directly as output. As described above, the direct use may be an output to an output panel to present the item to the user, or into the program itself for which the item is desired; this may also include mapping the recognizer's returned value to another identifier.

If a character was recognized at step <b>2004</b>, step <b>2004</b> branches to step <b>2006</b> where the character is used as a keyword (or to build a keyword) for searching, as described above. Step <b>2008</b> represents searching and obtaining the search results, with step <b>2012</b> representing presenting the found item or items to the user. Note that step <b>2010</b> is an optional step (as indicated by the dashed block and line) as described above, e.g., a single returned item found via a keyword search may be used directly such as by inserting it into the underlying program for which the search was requested and performed.

Exemplary Operating Environment

<figref idrefs="DRAWINGS">FIG. 21</figref> illustrates an example of a suitable computing system environment <b>2100</b> on which the unified digital ink search of <figref idrefs="DRAWINGS">FIGS. 19 and 20</figref> may be implemented. The computing system environment <b>2100</b> is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the computing environment <b>2100</b> be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment <b>2100</b>.

The invention is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the invention include, but are not limited to: personal computers, server computers, hand-held or laptop devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.

The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and so forth, which perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in local and/or remote computer storage media including memory storage devices.

With reference to <figref idrefs="DRAWINGS">FIG. 21</figref>, an exemplary system for implementing various aspects of the invention may include a general purpose computing device in the form of a computer <b>2110</b>. Components of the computer <b>2110</b> may include, but are not limited to, a processing unit <b>2120</b>, a system memory <b>2130</b>, and a system bus <b>2121</b> that couples various system components including the system memory to the processing unit <b>2120</b>. The system bus <b>2121</b> may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus.

The computer <b>2110</b> typically includes a variety of computer-readable media. Computer-readable media can be any available media that can be accessed by the computer <b>2110</b> and includes both volatile and nonvolatile media, and removable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by the computer <b>2110</b>. Communication media typically embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of the any of the above should also be included within the scope of computer-readable media.

The system memory <b>2130</b> includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) <b>2131</b> and random access memory (RAM) <b>2132</b>. A basic input/output system <b>2133</b> (BIOS), containing the basic routines that help to transfer information between elements within computer <b>2110</b>, such as during start-up, is typically stored in ROM <b>2131</b>. RAM <b>2132</b> typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit <b>2120</b>. By way of example, and not limitation, <figref idrefs="DRAWINGS">FIG. 21</figref> illustrates operating system <b>2134</b>, application programs <b>2135</b>, other program modules <b>2136</b> and program data <b>2137</b>.

The computer <b>2110</b> may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, <figref idrefs="DRAWINGS">FIG. 21</figref> illustrates a hard disk drive <b>2141</b> that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive <b>2151</b> that reads from or writes to a removable, nonvolatile magnetic disk <b>2152</b>, and an optical disk drive <b>2155</b> that reads from or writes to a removable, nonvolatile optical disk <b>2156</b> such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive <b>2141</b> is typically connected to the system bus <b>2121</b> through a non-removable memory interface such as interface <b>2140</b>, and magnetic disk drive <b>2151</b> and optical disk drive <b>2155</b> are typically connected to the system bus <b>2121</b> by a removable memory interface, such as interface <b>2150</b>.

The drives and their associated computer storage media, described above and illustrated in <figref idrefs="DRAWINGS">FIG. 21</figref>, provide storage of computer-readable instructions, data structures, program modules and other data for the computer <b>2110</b>. In <figref idrefs="DRAWINGS">FIG. 21</figref>, for example, hard disk drive <b>2141</b> is illustrated as storing operating system <b>2144</b>, application programs <b>2145</b>, other program modules <b>2146</b> and program data <b>2147</b>. Note that these components can either be the same as or different from operating system <b>2134</b>, application programs <b>2135</b>, other program modules <b>2136</b>, and program data <b>2137</b>. Operating system <b>2144</b>, application programs <b>2145</b>, other program modules <b>2146</b>, and program data <b>2147</b> are given different numbers herein to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer <b>2110</b> through input devices such as a tablet, or electronic digitizer, <b>2164</b>, a microphone <b>2163</b>, a keyboard <b>2162</b> and pointing device <b>2161</b>, commonly referred to as mouse, trackball or touch pad. Other input devices not shown in <figref idrefs="DRAWINGS">FIG. 21</figref> may include a joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit <b>2120</b> through a user input interface <b>2160</b> that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB). A monitor <b>2191</b> or other type of display device is also connected to the system bus <b>2121</b> via an interface, such as a video interface <b>2190</b>. The monitor <b>2191</b> may also be integrated with a touch-screen panel or the like. Note that the monitor and/or touch screen panel can be physically coupled to a housing in which the computing device <b>2110</b> is incorporated, such as in a tablet-type personal computer. In addition, computers such as the computing device <b>2110</b> may also include other peripheral output devices such as speakers <b>2195</b> and printer <b>2196</b>, which may be connected through an output peripheral interface <b>2194</b> or the like.

The computer <b>2110</b> may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer <b>2180</b>. The remote computer <b>2180</b> may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer <b>2110</b>, although only a memory storage device <b>2181</b> has been illustrated in <figref idrefs="DRAWINGS">FIG. 21</figref>. The logical connections depicted in <figref idrefs="DRAWINGS">FIG. 21</figref> include one or more local area networks (LAN) <b>2171</b> and one or more wide area networks (WAN) <b>2173</b>, but may also include other networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.

When used in a LAN networking environment, the computer <b>2110</b> is connected to the LAN <b>2171</b> through a network interface or adapter <b>2170</b>. When used in a WAN networking environment, the computer <b>2110</b> typically includes a modem <b>2172</b> or other means for establishing communications over the WAN <b>2173</b>, such as the Internet. The modem <b>2172</b>, which may be internal or external, may be connected to the system bus <b>2121</b> via the user input interface <b>2160</b> or other appropriate mechanism. A wireless networking component <b>2174</b> such as comprising an interface and antenna may be coupled through a suitable device such as an access point or peer computer to a WAN or LAN. In a networked environment, program modules depicted relative to the computer <b>2110</b>, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation, <figref idrefs="DRAWINGS">FIG. 21</figref> illustrates remote application programs <b>2185</b> as residing on memory device <b>2181</b>. It may be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.

An auxiliary subsystem <b>2199</b> (e.g., for auxiliary display of content) may be connected via the user interface <b>2160</b> to allow data such as program content, system status and event notifications to be provided to the user, even if the main portions of the computer system are in a low power state. The auxiliary subsystem <b>2199</b> may be connected to the modem <b>2172</b> and/or network interface <b>2170</b> to allow communication between these systems while the main processing unit <b>2120</b> is in a low power state.

CONCLUSION

While the invention is susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific forms disclosed, but on the contrary, the intention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention.